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Modelling and Mapping of Aboveground Carbon of Oluwa Forest Reserve Using LandSat 8 TM and Forest Inventory Data

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This study was conducted in Oluwa Forest Reserve to assess and predict its aboveground carbon sequestration potentials using LandSat Thematic Mapper data. The Oluwa Forest Reserve, Ondo State, Nigeria, is recognized for its rich biodiversity and extensive size. To estimate its forest aboveground biomass and carbon should be complex and costly endeavour requiring the expertise of various professionals and equipment. Consequently, this study explored the use of Geographic Information System (GIS) and Remote Sensing (RS) technology using LandSat bands to estimate spectral indices in fitting linear models to predict the aboveground carbon sequestration potentials of the tropical rainforest ecosystem of Oluwa Forest Reserve. The observed aboveground carbon from sample plots and the estimated spectral indices were used to model the spread of aboveground carbon of Oluwa Forest Reserve. Positive linear relationship exists between the observed and the spectral indices data estimated. Therefore, linear models were fitted and the best-fit was determined using statistical measures. The aboveground carbon average estimated from the sample plots and the predicted were 150.70 t/ha and 149.80 t/ha, respectively. The coefficient of determination 94% and Root Mean Square Error = 6.38E-16, respectively were obtained statistically. The chosen model predicts the aboveground carbon spread of Oluwa Forest Reserve adequately. The study revealed that spectral data, GIS and RS are critical for large forest aboveground carbon modelling and mapping for efficiency.
Title: Modelling and Mapping of Aboveground Carbon of Oluwa Forest Reserve Using LandSat 8 TM and Forest Inventory Data
Description:
This study was conducted in Oluwa Forest Reserve to assess and predict its aboveground carbon sequestration potentials using LandSat Thematic Mapper data.
The Oluwa Forest Reserve, Ondo State, Nigeria, is recognized for its rich biodiversity and extensive size.
To estimate its forest aboveground biomass and carbon should be complex and costly endeavour requiring the expertise of various professionals and equipment.
Consequently, this study explored the use of Geographic Information System (GIS) and Remote Sensing (RS) technology using LandSat bands to estimate spectral indices in fitting linear models to predict the aboveground carbon sequestration potentials of the tropical rainforest ecosystem of Oluwa Forest Reserve.
The observed aboveground carbon from sample plots and the estimated spectral indices were used to model the spread of aboveground carbon of Oluwa Forest Reserve.
Positive linear relationship exists between the observed and the spectral indices data estimated.
Therefore, linear models were fitted and the best-fit was determined using statistical measures.
The aboveground carbon average estimated from the sample plots and the predicted were 150.
70 t/ha and 149.
80 t/ha, respectively.
The coefficient of determination 94% and Root Mean Square Error = 6.
38E-16, respectively were obtained statistically.
The chosen model predicts the aboveground carbon spread of Oluwa Forest Reserve adequately.
The study revealed that spectral data, GIS and RS are critical for large forest aboveground carbon modelling and mapping for efficiency.

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